Publications by authors named "Da-Lin Yuan"

Tangerine peels are herbal materials of two coupled traditional Chinese medicines, Pericarpium Citri Reticulatae (PCR) and Pericarpium Citri Reticulatae Viride (PCRV). In this paper, high-performance liquid chromatographic fingerprints of tangerine peels during growth were firstly measured for deliberately collected 34 samples from three species (Citrus reticulata 'Chachi', Citrus reticulata 'Dahongpao' and Citrus erythrosa Tanaka). After sixteen characteristic components which have similar change trends in the grown process were screened out with the help of heuristic evolving latent projection (HELP) method, score plots of principal component analysis (PCA) successfully presented the grown footprints of tangerine peels.

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High-performance liquid chromatographic (HPLC) fingerprints of pericarpium citri reticulatae (PCR) and pericarpium citri reticulatae viride (PCRV) were firstly measured for deliberately collected 39 authentic samples and 21 commercial samples. Both correlation coefficients of similarity for chromatograms and absolute peak areas of characteristic compounds were calculated for quantitative expression of the HPLC fingerprints. After principal component analysis (PCA) successfully distinguished the 'mixed peels' samples from authentic samples, partial least squares-linear discrimination analysis (PLS-LDA) was then effectively applied to class separation between authentic PCR and PCRV.

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In order to make programmed-temperature retention index (PTRI) data be shared by other chromatographers and laboratories, conversion of PTRI from one set of experimental conditions to another is investigated in detail in this work. It was found that the differences between the PTRIs at different heating rates are structurally dependent, especially the number of ring in molecules. Thus, with the help of molecule constitutional descriptors, equations of PTRI conversion to certain initial temperature, heating rate, and stationary phase were obtained with high correlation coefficients and low standard deviations.

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Metabolic profiling has increasingly been used as a probe in disease diagnosis and pharmacological analysis. Herein, plasma fatty acid metabolic profiling including non-esterified fatty acid (NEFA) and esterified fatty acid (EFA) was investigated using gas chromatography/mass spectrometry (GC/MS) followed by multivariate statistical analysis. Partial least squares-linear discrimination analysis (PLS-LDA) model was established and validated to pattern discrimination between type 2 diabetic mellitus (DM-2) patients and health controls, and to extract novel biomarker information.

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